Flower
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About
Flower is a flexible federated learning framework that enables the federation of any workload, utilizing various machine learning frameworks and programming languages. It showcases user-friendly tutorials and code examples to facilitate the implementation of federated learning concepts. Its scalability accommodates multiple clients, making it suitable for large-scale applications, and it operates seamlessly across cloud, mobile, and edge devices. Flower provides extensive documentation and an active community for support, making it accessible for both beginners and experienced developers.
Platform
Features
• platform independent
• ml framework agnostic
• user-friendly installation and usage
• bridges research and production
• compatible with cloud, mobile, and edge environments
• scalability for large numbers of clients
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A friendly federated learning framework supporting various ML frameworks and workloads.
A friendly federated learning framework supporting various ML frameworks and workloads.
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